static void Main(string[] args)
{
Console.Clear();
double[] real = new double[512];
double[] imag = new double[512];
double[] mag = new double[512];
double[] phase = new double[512];
Lomont.LomontFFT lom = new Lomont.LomontFFT();
double[] data = new double[1024];
lom.A = 1;
lom.B = -1;
for (int i = 0; i < 1024; i++)
{
data[i] = 30 * Math.Cos(2 * Math.PI * i / 16 + 3 * Math.PI / 2);
}
lom.RealFFT(data, true);
for (int i = 0; i < 512; i++)
{
real[i] = data[2 * i];
imag[i] = data[2 * i + 1];
}
for (int i = 0; i < 512; i++)
{
mag[i] = Math.Round(Math.Sqrt(Math.Pow(real[i], 2) + Math.Pow(imag[i], 2)) / 1024);
phase[i] = Math.Round(Math.Atan2(imag[i], real[i]) * 180 / Math.PI);
}
for (int i = 0; i < 512; i++)
{
Console.WriteLine(i + ". " + "mag: " + mag[i] + " phase: " + phase[i]);
}
}
public static Complex[] ConvertToFreq(double[] timeData)
{
//Get the size of next power of 2
int length = timeData.Length;
int root = (int)Math.Log(length, 2);
root += 1;
int paddedLength = (int)Math.Pow(2, root);
//Create an array that is a power of 2 and copy the values over.
//Pad the end of the array with zeros
double[] paddedData = new double[paddedLength];
for(int i=0; i<paddedLength; i++)
{
if(i < length)
paddedData[i] = timeData[i];
else
paddedData[i] = 0;
}
//Do the FFT
Lomont.LomontFFT lomontFft = new Lomont.LomontFFT();
lomontFft.RealFFT(paddedData, true);
//Convert everything to the complex data type
Complex[] freqData = new Complex[paddedLength / 2];
for (int i = 0; i < freqData.Length; i++)
{
freqData[i] = new Complex(paddedData[i], paddedData[i + 1]);
}
return freqData;
}
public List <SpectralImage> CreateLogSpectrogram(AudioSamples audioSamples, SpectrogramConfig configuration)
{
using (new DebugTimer("CreateLogSpectrogram()"))
{
int wdftSize = configuration.WdftSize;
int width = (audioSamples.Samples.Length - wdftSize) / configuration.Overlap;
if (width < 1)
{
return(new List <SpectralImage>());
}
float[] frames = new float[width * configuration.LogBins];
ushort[] logFrequenciesIndexes = logUtility.GenerateLogFrequenciesRanges(audioSamples.SampleRate, configuration);
float[] window = configuration.Window.GetWindow(wdftSize);
float[] samples = audioSamples.Samples;
// PIN: reverted the following FFT to use lomontFFT with managed code (not the unsafe changed made by the original author due to the issues on my computers)
// NOTE! When using Parallell.For the result becomes different from time to time
// when running in Release mode.
// Therefore make sure to use for loop instead
for (int index = 0; index < width; index++)
// Parallel.For(0, width, index =>
{
var fftArray = CopyAndWindow(samples, index * configuration.Overlap, window);
lomontFFT.RealFFT(fftArray, true);
// after the lomont realfft the fft input array will contain the FFT values
// r0, r(n/2), r1, i1, r2, i2 ...
// since the extract log bins method only uses lowBound index above 2 we can ignore the fact
// that the first and second values are "special": r0, r(n/2)
// see https://github.com/perivar/FindSimilar/blob/6b658b1c54d1504136e25e933f39b7c303da5d9e/Mirage/Fft.cs
ExtractLogBins(fftArray, logFrequenciesIndexes, configuration.LogBins, wdftSize, frames, index);
}
// );
if (configuration.Verbosity == Verbosity.Verbose)
{
var imageService = new FindSimilarImageService();
using (Image image = imageService.GetSpectrogramImage(frames, width, configuration.LogBins, width, configuration.LogBins))
{
var fileName = Path.Combine(SoundFingerprinter.DEBUG_DIRECTORY_PATH, (Path.GetFileNameWithoutExtension(audioSamples.Origin) + "_spectrogram.png"));
if (fileName != null)
{
image.Save(fileName, ImageFormat.Png);
}
}
WriteOutputUtils.WriteCSV(frames, Path.Combine(SoundFingerprinter.DEBUG_DIRECTORY_PATH, (Path.GetFileNameWithoutExtension(audioSamples.Origin) + "_frames.csv")));
}
var spectralImages = CutLogarithmizedSpectrum(frames, audioSamples.SampleRate, configuration);
if (configuration.Verbosity == Verbosity.Verbose)
{
if (spectralImages.Count > 0)
{
var spectralImageList = new List <float[]>();
foreach (var spectralImage in spectralImages)
{
spectralImageList.Add(spectralImage.Image);
}
var spectralImageArray = spectralImageList.ToArray();
WriteOutputUtils.WriteCSV(spectralImageArray, Path.Combine(SoundFingerprinter.DEBUG_DIRECTORY_PATH, (Path.GetFileNameWithoutExtension(audioSamples.Origin) + "_spectral_images.csv")), ";");
}
}
ScaleFullSpectrum(spectralImages, configuration);
return(spectralImages);
}
}
public static void FindPhaseByFFT(IEnumerable<double> inputSignal, double sampelingFrequency, double baseFrequency)
{
Lomont.LomontFFT x = new Lomont.LomontFFT();
double[] pow2array = new double[1024];
for (double i = 0; i < 1024; i++)
{
pow2array[(int) i] = Math.Cos(i * 250e3 / (2 * Math.PI));
}
double a1, a2;
a1 = pow2array[10];
x.RealFFT(pow2array, true);
a2 = pow2array[10];
//x.FFTPhaseFinder()
a2 = pow2array[10];
}